Security

Threat modeling is the most powerful, underutilized, easy-to-do security methodology we have: why isn’t everybody doing it already, or why do those who are keep their work secret? If you already threat model your digital systems and products, and are doing the work already then you are doing security right so you should share it with pride. Publishing threat models may be the best evidence of excellent security work that customers and users can appreciate the value of, short of a rigorous detailed design and code review. You’ve already done the work — or if not you really should — and making it public not only is great promotion but it also helps all stakeholders understand their respective roles and responsibilities in securing larger systems. (about 4600 words)

Demand more

I applaud CISA leadership speaking out aggressively at the mWISE Conference 2024 about the dismal state of software security (based on reporting in The Register, but it would be nice for www.cisa.gov to publish transcripts in order to ensure we are interpreting remarks with full context, given that the videos are paywalled).

(2300 words) Threat modeling isn’t just for software security; you can even threat model threat modeling. When a major software incident occurs, the first thing we should be asking is “show us the threat model”.

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In a debunking blog post, Crowdstrike finally starts to describe that content files are digitally signed for deployment. The initial report oddly referenced file timestamps instead of hashes to designate the bad and good versions of the infamous Channel File 291, but now we know these were signed.

The Crowdstrike July incident root cause analysis report provides new detail and requires reading between the lines to interpret (I welcome corrections with references if I got it wrong).

Say what you will about LLM technology, it’s remarkable that we can do computations on the scale of billions of parameters training on large chunks of humanity’s collective text and media at all — and then it’s remarkable how you can talk to “it” in everyday language and get any kind of recognizable response out of it all, often (but not always) a pretty good one, and this is all based on the simple but powerful “select the best next token” algorithm run in a loop. The concept would have made a terrific sci-fi series, and here we are with it working in our cloud at scale.

July 30, 2024 — When will we address the unacceptable status quo of scam phone calls, SMS text, and email?

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Threat modeling methodology centers on asking, “What could go wrong?” and then considering mitigations to address such an eventuality. The unending calamities of history vividly demonstrate how human intuition repeatedly fails to foresee many such events until after they happen, and even then we sometimes fail to learn and act. For example, consider the 2008 financial crisis: after all the bailout money was handed out around Wall Street, Congress never confronted the glaringly obvious problem of “too big to fail” institutions. As a result, large firms continued to consolidate, concentrating power and risk in still fewer institutions, creating conditions for a repetition that appears to be a matter of “when” rather than “if”. Traditionally threat modeling has been deployed exclusively within the context of secure software engineering, but I posit that it is just as effective and important a tool for anticipating potential harms of all kinds — not just malicious exploitations.

Secret questions as credentials for online account authentication are simply a bad idea in my view: I have never seen them done well, often seem them done atrociously, and my most generous assessment would be that they are extremely hard to do well. But keeping an open mind, here's a brief reasoning why these are problematic, and I invite anyone interested to do a brilliant design and prove me wrong.

ProPublica is a national journalistic treasure, and recent reporting on the software industry is a terrific impetus to drive much needed change. I sat in on many bug triage discussions over twenty years ago working at Microsoft, and despite great technology advances, the way these decisions are made appears to be little evolved. My purpose here is not to judge what transpired and who is at fault, but to glean from the reporting better software practices so we can at least learn from these events.